Evidence map›Paper›PMID 32932205›Full record

ArticleDevelopmental cognitive neuroscience2020

Temporal dynamics of visual representations in the infant brain.

Laurie Bayet, Benjamin D Zinszer, Emily Reilly, Julia K Cataldo, Zoe Pruitt, Radoslaw M Cichy, Charles A Nelson, Richard N Aslin

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Developmental cognitive neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
  2. Article
  3. Deep learning in fetal, infant, and toddler neuroimaging research.Developmental cognitive neuroscience · 2026
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Development of Higher-Level Vision: A Network Perspective.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 6 institutions in 2 countries.

Laurie BayetDepartment of Psychology, American University, Washington, DC, 20016, USA; Center for Neuroscience and Behavior, American University, Washington, DC, 20016, USA. Electronic address: bayet@american.edu.
Benjamin D ZinszerDepartment of Psychology, Princeton University, Princeton, NJ, 08540, USA; Department of Linguistics and Cognitive Science, University of Delaware, Newark, DE, 19716, USA.
Emily ReillyBoston Children's Hospital, Boston, MA, 02115, USA.
Julia K CataldoBoston Children's Hospital, Boston, MA, 02115, USA.
Zoe PruittDepartment of Brain and Cognitive Science, University of Rochester, Rochester, NY, 14627, USA.
Radoslaw M CichyDepartment of Education and Psychology, Freie Universität Berlin, 14195, Berlin, Germany.
Charles A NelsonBoston Children's Hospital, Boston, MA, 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA, 02115, USA; Graduate School of Education, Harvard, Cambridge, MA, 02138, USA.
Richard N AslinHaskins Laboratories, 300 George Street, New Haven, CT, 06511, USA; Psychological Sciences Department, University of Connecticut, Storrs, CT, 06269, USA; Department of Psychology, Yale University, New Haven, CT, 06511, USA; Yale Child Study Center, School of Medicine, New Haven, CT, 06519, USA.
Boston Children's Hospital · USAmerican University · USFreie Universität Berlin · DEHaskins Laboratories · USPrinceton University · USUniversity of Rochester · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

Tools from computational neuroscience have facilitated the investigation of the neural correlates of mental representations. However, access to the representational content of neural activations early in life has remained limited. We asked whether patterns of neural activity elicited by complex visual stimuli (animals, human body) could be decoded from EEG data gathered from 12-15-month-old infants and adult controls. We assessed pairwise classification accuracy at each time-point after stimulus onset, for individual infants and adults. Classification accuracies rose above chance in both groups, within 500 ms. In contrast to adults, neural representations in infants were not linearly separable across visual domains. Representations were similar within, but not across, age groups. These findings suggest a developmental reorganization of visual representations between the second year of life and adulthood and provide a promising proof-of-concept for the feasibility of decoding EEG data within-subject to assess how the infant brain dynamically represents visual objects.

Indexed as

AdolescentAdultBrainFemaleHumansInfantMalePattern Recognition, VisualYoung AdultAnimalsBodyDecodingDevelopmentEEGInfantObjectsRepresentationRSAVision

Identifiers

PMID32932205
PMCPMC7498752
OpenAlexW3084311690

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.